• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1528-1528
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• 2001

Ginseng cultivated in different country or growing condition has generally different components such as saponin and protein, and it relates to efficacy and action. Protein content assumes by nitrogen content in ginseng radix. Nitrogen content could be determined by chemical analysis such as kjeldahl or extraction methods. However, these methods require long analysis time and result environmental pollution and sample damage. In this work we investigated possibility of non-destructive determination of nitrogen content in ginseng radix using near-infrared spectroscopy. Ginseng radix, root of Panax ginseng C. A. Meyer, was studied. Total 120 samples were used in this study and it was consisted of 6 sample sets, 4, 5 and 6-year-old Korea ginseng and 7, 8 and 9-year-old China ginseng, respectively. Each sample set has 20 sample. Nigrogen content was measured by electronic analysis. NIR reflectance spectra were collected over the 1100 to 2500 nm spectral region with a InfraAlyzer 500C (Bran+Luebbe, Germany) equipped with a halogen lapmp and PbS detector and data were collected every 2 nm data point intervals. The calibration models were carried out by multiple linear regression (MLR) and partial least squares (PLS) analysis using IDAS and SESAME software. Result of electronic analysis, Korean ginseng were different mean value in nitrogen content of China ginseng. Ginseng tend to generally decrease the nitrogen content according as cultivation year is over 6 years. The MLR calibration model with 8 wavelengths using IDAS software accurately predicted nitrogen contents with correlation coefficient (R) and standard error of prediction of 0.985 and 0.855%, respectively. In case of SESAME software, the MLR calibration with 9 wavelength was selected the best calibration, R and SEP were 0.972 and 0.596%, respectively. The PLSR calibration model result in 0.969 of R and 0.630 of RMSEP. This study shows the NIR spectroscopy could be applied to determine the nitrogen content in ginseng radix with high accuracy.

• Human Ecology Research
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• v.60 no.1
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• pp.1-20
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• 2022

This paper presents a social network analysis of changes in Home Economics education content loaded on YouTube before and after the outbreak of COVID-19. From January 1, 2008 to June 30, 2021, a basic analysis was conducted of 761 Home Economics education videos loaded on YouTube, using NetMiner 4.3 to analyze important keywords and the centrality of video titles and full texts. Before COVID-19, there were 164 Home Economics education videos posted on YouTube, increasing significantly to 597 following the emergence of the pandemic. In both periods, there was more middle school content than high school content. The content in the child-family field was the most, and the main keywords were youth and family. Before COVID-19, a performance evaluation indicated that the proportion of student content was high, whereas after the outbreak of the disease, teacher content increased significantly due to the effect of distance learning. However, compared with video use, the self-expression and participation of users were lower in both periods. The centrality analysis indicated that in the title, 'family' exhibited a high degree of both centrality and eigenvector centrality over the entire period. Degree centrality of the video title was found to be high in the order of class, online, family, management, etc. after the outbreak of COVID-19, and the connection of keywords was strong overall. Eigenvector centrality indicated that career, search, life, and design were influential keywords before COVID-19, while class, youth, online, and development were influential keywords after COVID-19.

• Journal of Environmental Impact Assessment
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• v.6 no.2
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• pp.165-180
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• 1997

Mitigation measures in EIS are the important factors in the effectiveness of EIS. This paper analyzed the content of mitigation measures described in the 30 EISs selected, using 7 analysis items in order to discover the degree of effectiveness of mitigation measures. 30 EISs used in this study were selected through variance maximization strategy, and the 7 analysis items were; 1) thoroughness of mitigation content, 2) quantification of mitigation content, 3) explicit description of mitigation effect, 4) likelihood of mitigation effect, 5) impacted area of mitigation effect, 6) time frame of mitigation effect, and 7) environmental impact of mitigation measures. The results showed that the effectiveness of mitigation measures in the analyzed EISs was relatively low both in the appropriateness and in the specificity. It was suggested that in order to improve the appropriateness of EIS as a decision making tool, the effect of mitigation measures, as well as the mitigation measures themselves, should be studied and described more thoroughly and specifically.

• 보존과학연구
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• s.31
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• pp.131-140
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• 2010

This study shows the comparison of chemical compositions of main component with other bronze bells after the research on the component analysis by non-destructive XRF analysis. There are shrinkage cavities caused by the shrinkage defect and pores with pollutants on Bronze Bell of Heungguksa Temple with gamma radiation images and 77.3% of copper, 8.4% of tin and 10.9% of lead were determined as the main components of it with XRF analysis The tin content of Brozen Bell of Heungguksa Temple is less than those (11~18%) of other bronze bells but the lead content of that is higher. The lead content of it shows 10.91% which is quite high while generally the lead contents of other bells were controlled lower than 2.1%. Buddhist bells have the different lead content according to the period. The lead content was low until Silla Dynasty and Unified Silla period but it has been getting higher since some point of Koryo Dynasty. It is assumed that expensive copper and tin were replaced with lead.

• Journal of Convergence for Information Technology
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• v.10 no.9
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• pp.251-261
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• 2020

The purpose of this research is to examine the relationship between motivation, reliability, satisfaction, and sustainability of YouTube content and suggest the implications needed for content consumption or production of beauty workers in the future as K-beauty's interest is increasing due to the global Hallyu craze, and beauty industry workers are also watching YouTube hair care content and exchanging the latest trends. The analysis methods included frequency analysis, factor analysis, reliability analysis, correlation analysis, and multi-recovery analysis. As a result, the correlation between the motivation for content use, reliability, satisfaction, and persistence was shown, the motivation for content use was statistically significant (+) and the impact of content reliability on YouTube content satisfaction and sustainability (a significant statistical+).

• Journal of Applied Biological Chemistry
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• v.66
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• pp.305-310
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• 2023

Bandiburichodang (BDC) is a new variety of Zea mays L. Total polyphenol content (TPC) assay and quantitative analysis of ferulic acid (FA) were performed to determine the steaming, roasting conditions of BDC kernels that lead to the highest content. TPC levels increased after roasting under all conditions. TPC levels in samples steamed at 115 ℃ for 25 min were 3.157 mg/g before roasted, and increased to 3.825 and 4.739 mg/g after roasting at 160 and 200 ℃, respectively. Whether BDC kernels were roasted was relevant with TPC content. BDC kernels were extracted to perform quantitative analysis of FA. Roasting temperature affected FA content: the higher the temperature, the lower the content. BDC kernels that were steamed at 115 ℃ for 25 min had 0.178 mg/g of FA content before roasting, and levels decreased to 0.132 and 0.115 mg/g after roasting. Under different roasting conditions, FA content decreased 15 to 50%. We hypothesize that this phenomenon is due to a breakdown of phenolic compounds or cell wall disruption.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.326-331
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• 2023

Korea's cultural content industry can develop into another unique tourism industry. However, since other prior studies focus on the Japanese content industry, this study identifies modern industrial trends by combining the unique characteristics of Korean content, that is, cultural content tourism, and the analysis ability of big data. The current status and direction of the cultural content tourism industry were studied by utilizing the extensive information collection and in-depth analysis capabilities of big data, and as a result, it was confirmed that the trend of the cultural content industry is related to the business aspect of cultural content, not the pure content interest of cultural content. This shows that Korean cultural contents have a strong business aspect. As a limitation, when research design was conducted using social media big data, the age, gender, etc. of the subject analyzed with unique anonymity could not be known. The Korean cultural content industry is expected to be successful in terms of business.

• Journal of Korean Society for Quality Management
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• v.48 no.3
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• pp.433-451
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• 2020

Purpose: The purpose of this study is to investigate how the type of virtual reality content production affects the interaction and immersion that is a virtual reality characteristic, and to provide the platform companies and content producers with the basic information necessary to provide the production and service of content suitable for VR characteristics. Methods: Based on the data collected in the survey, multiple regression analysis and hierarchical regression analysis were used. The measurement tools used in this study were studied through three-dimensional composition, including the characteristics and interaction and immersion of content produced in 2D, 3D and 360°, which are elements of virtual reality characteristics. Results: The results of this study are as follows. Among the types of content production, content produced with 2D and 360 technologies was found to affect immersion, while content produced in 3D affected interaction. Motion sickness has been investigated to affect both immersion and interaction. Conclusion: Service-provided platform enterprises and content-making enterprises should consider content-making and providing services that suit service characteristics and purposes, taking into account the characteristics of interaction and immersion in content-making investment and service delivery.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.303-312
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• 2022

In this study, the importance-performance analysis (IPA) of the content components of remote graduate students was conducted. To this end, an online survey of 221 remote graduate students at J University obtained the following results. First, the importance of content components by area was in the order of learning content, interaction, teaching-learning strategy, and evaluation, and the degree of execution was in the order of teaching-learning strategy, interaction, evaluation, and learning content. Second, it was found that there were significant differences between importance and performance in the four areas of content components: learning content, teaching-learning strategy, interaction, and evaluation. The importance-execution analysis (IPA) was conducted in two dimensions: region-specific and item-specific, and the results are as follows. The learning content was found to be the maintenance area, the teaching-learning strategy and interaction were the key improvement areas, and the evaluation area was the overinvestment area. The results of this study can be used as basic data to diagnose the present of remote graduate school content and to gauge what needs to be improved in the future based on it.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.735-745
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• 2013

The emergence of Web 2.0 technologies, such as blogs and wiki, enable even naive users to easily create and share content on the Web using freely available content sharing tools. Wide availability of almost free data and promiscuous sharing of content through social networking platforms created a content borrowing phenomenon, where the same content appears (in many cases in the form of extensive quotations) in different outlets. An immediate side effect of this phenomenon is that identifying which content is re-used by whom is becoming a critical tool in social network analysis, including expert identification and analysis of information flow. Internet-scale reuse detection, however, poses extremely challenging scalability issues: considering the large size of user created data on the web, it is essential that the techniques developed for content-reuse detection should be fast and scalable. Thus, in this paper, we propose a $qSign_{lsh}$ algorithm, a mechanism for identifying multi-sentence content reuse among documents by efficiently combining sentence-level evidences. The experiment results show that $qSign_{lsh}$ significantly improves the reuse detection speed and provides high recall.